Job Summary
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Required Skills |
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• Strong hands-on experience with Python, SQL, PySpark, and distributed data processing. |
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• AWS experience across Glue, EMR, S3 and working knowledge of SageMaker, Lambda, Step Functions, DynamoDB, RDS. |
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• Strong SQL skills; experience with data warehousing concepts and platforms such as Snowflake. |
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• Experience with workflow orchestration (e.g., Airflow) and production-grade pipeline operations. |
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• Experience with Kafka or other event streaming technologies. |
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• Understanding of data modeling, pipeline reliability, and performance optimization. |
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• CI/CD with GitLab, containerization (Docker), and infrastructure automation (Terraform/CloudFormation). |
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Good-to-Have |
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• Exposure to Banking domain; experience in Financial Crime / AML / Fraud analytics is a plus. |
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• Exposure to regulatory expectations around model risk management and auditability. |
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• Experience with interpretability, monitoring, and drift detection concepts/frameworks. |
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• Nice-to-have: Informatica Data Management Cloud (IDMC) exposure or migration context. |
Key Responsibilities
Skill Requirements
|
Required Skills |
|
• Strong hands-on experience with Python, SQL, PySpark, and distributed data processing. |
|
• AWS experience across Glue, EMR, S3 and working knowledge of SageMaker, Lambda, Step Functions, DynamoDB, RDS. |
|
• Strong SQL skills; experience with data warehousing concepts and platforms such as Snowflake. |
|
• Experience with workflow orchestration (e.g., Airflow) and production-grade pipeline operations. |
|
• Experience with Kafka or other event streaming technologies. |
|
• Understanding of data modeling, pipeline reliability, and performance optimization. |
|
• CI/CD with GitLab, containerization (Docker), and infrastructure automation (Terraform/CloudFormation). |